# Stefan Kløvning

Stefan Kløvning shares practical guidance on business software, system integration, and enterprise AI. Kløvning's posts explain how to choose an integration approach, prepare for software outages, and assess whether agentic AI fits a business process.

- Profile: https://b2binfluencer.marketing/creators/stefan-kl-vning/
- LinkedIn: https://www.linkedin.com/in/stefankl%C3%B8vning
- Topics: artificial-intelligence, agentic-ai, ai-adoption
- Based on 11 dated posts, latest 2026-10-08

## Summary

Practical guidance on business software, system integration, and enterprise AI decisions.

- Best for: A B2B software consultancy campaign on AI compliance and system integration.
- Not for: A brand wanting fixed sponsored product posts with reach guarantees and on-camera demos.
- Check first: Ask for recent LinkedIn audience analytics and sponsorship terms before contacting them.

### Takeaways

- Integration post compares no-code, low-code, and full-code, warning full-code is not automatically better.
- Cloudflare outage post says third-party dependency is a trade-off to prepare for.
- Agentic AI post asks if it is the right tool before asking if it works.

## Main ideas

- **Match the integration approach to the workflow, not to how serious the work looks**: Kløvning argues that the choice between no-code, low-code, and full-code should follow the workflow, not a prestige ranking of methods. No-code suits a simple, standardized flow built from ready-made connectors. Low-code suits a flow built mainly visually but requiring extra logic. Full-code suits complex or business-critical integrations where developers build a tailored solution across several systems, with custom rules, security, and failure handling. The same tool can function as no-code in one workflow and low-code in another; full-code is not automatically better than no-code. The aim is not maximum automation, but avoiding repeated data entry and making systems easier to trust.
- **Third-party dependency is a trade-off to prepare for, not a problem to solve**: When Cloudflare's network failed and took major applications down with it, Kløvning did not call for abandoning third-party platforms. They argue that modern software depends on existing frameworks, dependencies, and code because building everything yourself would be far more expensive and slower, and there is no simple way to remove that exposure entirely. What organizations can do is prepare: map and review risks continually, establish backups and alternatives, set up crisis and contingency protocols, and train people to use them. Kløvning also warns about lightly engineered, quickly built applications, noting that the same failure hit globally funded platforms.
- **Ask whether agentic AI is the right tool before asking whether it works**: Kløvning frames the enterprise agentic AI decision around two questions that matter more than the hype. First, is the organization ready to invest in the cybersecurity, infrastructure, and oversight that enterprise-ready agentic AI requires? Second, is agentic AI the right tool, given that workflow automation, retrieval-augmented generation, prediction models, computer vision, recommendation systems, and OCR each solve specific problems more efficiently and with less risk exposure? The promised output is a checklist for matching each technique to the problem it suits, not a verdict on agents.
- **AI adoption is a compliance question, and the legal side is specialist work**: Kløvning treats regulation and security as part of AI adoption, not as constraints to handle afterward. Announcing a webinar their company ran for the marketing company Synlighet, they describe its goal as applying AI efficiently while complying with existing and upcoming regulation, and understanding the risks and opportunities of responsible use. The content is attributed to legal specialist Legal Counsel Kohári Réka, who has 15 years of legal practice and specializes in ICT law. Kohári Réka led the presentation, covering the implications of GDPR and the EU AI Act for corporate AI use, practical aspects of responsible AI, contractual considerations with AI vendors, and cybersecurity measures.
- **Stalled delivery is often unblocked through people rather than support queues**: Kløvning describes a habit formed on the job: when a critical case is stuck with a third-party supplier and standard channels stop producing results, go directly to a person. Email, support portals, and phone follow-ups leave the ticket queued and bring generic replies. Instead, Kløvning searches for key people, product specialists, or customer success managers at the supplier, then sends a short, direct message explaining the situation and asking for guidance. The post treats a professional network as a delivery tool, not just a place to look for a job.
- **A recurring counterweight: Kløvning qualifies their recommendations**: Across the posts, Kløvning states a rule of thumb, then limits it rather than leaving the reader with a hierarchy. Full-code is not automatically better than no-code. Avoiding third-party platforms is unrealistic; the answer is mitigation. Agentic AI may be the wrong tool even when an organization is ready. Kløvning does not promote a single approach; the qualifications show where their judgment lies.

## Work to read

- [Choosing between no-code, low-code, and full-code integration](https://www.linkedin.com/posts/stefankl%C3%B8vning_systemintegrasjon-typer-activity-7505188942439227393-kvHv)
- [Two questions to ask before adopting agentic AI](https://www.linkedin.com/posts/stefankl%C3%B8vning_if-youre-considering-agentic-ai-for-an-enterprise-activity-7458481655595413504-VVbv)
- [What the Cloudflare outage says about software dependencies](https://www.linkedin.com/posts/stefankl%C3%B8vning_cloudflare-is-today-experiencing-issues-in-activity-7396556774675230720-rqW5)
- [Running an AI compliance webinar for a marketing company](https://www.linkedin.com/posts/stefankl%C3%B8vning_a-few-weeks-ago-we-at-nordic-ai-held-a-webinar-activity-7396886281881796608-x2sf)
- [Using LinkedIn to escalate a blocked support case](https://www.linkedin.com/posts/stefankl%C3%B8vning_linkedin-har-blitt-et-uventet-men-effektivt-activity-7513523944092680192-mJo9)

## Brand relationships

- **Nordic AI** (employment)
- **Com2.ai** (employment)
- **Synlighet** (client)

## Partnerships

Stefan Kløvning’s posts describe an educational collaboration offer rather than a published sponsorship programme. The clearest example is a webinar that Nordic AI, where they post, ran for the marketing company Synlighet on AI compliance and security. The session covered GDPR and the EU AI Act in corporate AI use, practical responsible-AI work, contractual questions with AI vendors and cybersecurity measures, and was presented by Nordic AI’s Legal Counsel. The same post invites organisations to request a similar webinar or workshop on AI compliance, security or implementation. The posts do not describe sponsored content, paid placements, rate cards, audience guarantees, exclusivity terms or a booking process. A software consultancy planning an AI-compliance or system-integration collaboration should treat the webinar or workshop as the format shown and agree scope directly.

## Alternatives

- Micky Weis: If the collaboration shifts from connecting systems to using AI in day-to-day commercial work, Micky Weis is the stronger partner for a campaign aimed at marketing and e-commerce teams. Both posts focus on implementation. One lays out a working setup — Claude, ChatGPT, Whisper Flow and BigQuery, with connectors to Shopify, Figma, Canva, Meta and Drive — and recommends keeping a folder per client with brand DNA, past ads and newsletters, then setting read-only data access before asking anything of the model. The other turns that approach into a pre-Q4 checklist: audit every email flow, check whether discount codes still hold, build top-of-funnel before performance spend, and connect Klaviyo and Meta data to review what worked in previous Black Friday and Christmas sales. A consultancy selling AI adoption to marketing and e-commerce teams gets teachable practice with named tools and a clear starting order, not architecture diagrams.
- John Nielsen: When the collaboration calls for security rather than AI governance, John Nielsen is the better fit. Both posts draw on measured findings and end with numbered actions. One explains the difference between penetration testing, red teaming and cyber security mystery shopping, illustrating it with an unescorted walk through the front door and a live network socket. It cites the National Bank of Denmark's TIBER-DK programme, running since January 2019, as the established version of that testing. It closes with three concrete steps, including network access control for unknown devices. The other reports that 663 of 798 surveyed Danish water utility domains do not tell recipients to reject mail sent in their name, that a free check has run 12,000 times across 10,850 domains, and that NIS2 has covered drinking water since 1 July 2025. It then asks who was responsible for testing and when leadership last saw the result. For an audience that values documented findings and audit-style questions, this is the most directly reusable material of the three.
- Christian Lunøe Gøtzsche: When the collaboration needs to reach commercial leadership — chief executives, commercial and strategy leads — and make AI compliance sound like a business decision, Christian Lunøe Gøtzsche is the strongest match. One post addresses that audience directly, framing compliance as guardrails that help a team move rather than paperwork that slows it. It poses two diagnostic questions: whether confidential go-to-market strategy and customer data are sitting in a free tier of a language model because it was convenient, and whether sales teams are ranking CRM leads through automated profiling of people's LinkedIn posts. The other outlines a five-agent architecture for a B2B rollout into the German market, with a compliance checkpoint before anything reaches the CRM, and asks whether an AI budget is being spent on the surface or the infrastructure. Together, the posts give a consultancy a leadership-level case for why governance work is worth buying.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/